Reconstructing objects in three dimensions from a set of two-dimensional images is a long standing problem in computer vision. And despite significant research efforts, objects with thin features still pose problems for many reasons. First, the thin features occupy only a small number of pixels in the views that they are visible in, making locating them difficult. Moreover, many object reconstruction techniques miss the thin features because the techniques require patches on the objects to be several pixels wide, which is not always the case with thin features. The thin features are also usually only visible in a small number of views, making matching the thin features between different views difficult. Other reconstruction techniques face difficulties with texture-less thin features because it is hard for such techniques to localize the features using photoconsistency values inside a volumetric discretization, often resulting in elimination of these features in the reconstruction. Therefore, there is a need in the art to improve techniques for reconstructing objects in three dimensions from a set of two-dimensional images.